神东矿区生态系统服务功能评价

Evaluation of ecosystem service function in Shendong mining area

  • 摘要: 神东矿区是中国重要的煤炭生产基地,煤炭开采对其脆弱的生态环境造成了强烈扰动,亟需利用科学手段揭示神东矿区生态系统服务功能的演变规律,完善矿区兼顾绿色开采与可持续发展的管理体系。为量化神东矿区生态系统服务功能的变化,并且基于InVEST模型集成水源供给、土壤保持、碳储存3项生态系统服务构建综合生态系统服务(Comprehensive Ecosystem Service,CES)评价模型,并且基于矿区尺度和矿井尺度综合测度神东矿区1990—2018年CES变化特征与规律。研究结果表明:在矿区尺度上,① 神东矿区SCE在时间上由0.448 6(1990年)下降到0.382 5(2000年),然后持续增加至0.471 6(2015年)又下降到0.453 2(2018年),整体以每年0.009的速度呈增加趋势;在空间上以西北部最弱,且由西北向东南部逐渐增强;② 神东矿区CES空间变化特征明显,低变区变化对CES变化的贡献力高于中变区和突变区,且CES的空间变化与植被覆盖和用地类型密切相关;③ 神东矿区CES空间聚类明显,呈现“西北部最弱、河流沿岸最强、东南部不显著”的格局;④ 神东矿区CES变化的驱动因子影响程度依次为土地利用类型、坡度、高程、降雨及植被覆盖度,双因子协同作用高于单因子,且土地利用与其他因子的协同作用最强。矿井尺度上,① 神东矿区CES以中强度开采区最高(SCE=0.502 8),极高强度开采区最低(SCE=0.430 8);② 补连塔矿井采区的CES受生态治理措施的正面影响,大柳塔、活鸡兔矿井采区的CES在2010年以后受到采矿的负面影响,石圪台、乌兰木伦、哈拉沟及榆家梁矿井采区的CES自采矿以来持续遭受负面影响;③ 大柳塔复垦实验区的CES往变强的方向发展。该模型的综合评估结果能够定量反映神东矿区CES的变化规律,建议神东矿区实施生态管理以西北部为重点区,以提高植被覆盖为导向优化土地利用格局,并利用矿区微生物复垦等科学方法改善矿区生态等。另外,应致力于多项生态系统服务多尺度优化集成模型的开发利用,以期为区域生态系统服务可持续管理提供更精准可靠的决策支持。

     

    Abstract: The Shendong mining area is an important coal production base in China,and the coal mining has caused strong disturbance to its fragile ecological environment.It is necessary to use scientific methods to reveal the evolution of the ecosystem service function of the Shendong mining area,and improve the management system of green mining and sustainable development in the mining area.To quantify the changes in ecosystem service functions in Shendong mining area,a Comprehensive Ecosystem Service (CES) evaluation model was constructed based on the InVEST model,which integrates three ecosystem services:water supply,soil conservation,and carbon storage,and measures the characteristics and patterns of changes in CES in the Shendong mining area from 1990 to 2018 in both the scale of mining area and mine.The results show that at the mining area scale,① the SCE in Shendong mining area decreased from 0.448 6 (1990) to 0.382 5 (2000),and then continued to increase to 0.471 6 (2015) and then decreased to 0.453 2 (2018),showing an overall increasing trend at a rate of 0.009 a-1.Spatially,it was the weakest in the northwest and gradually strengthened from the northwest to the southeast.② The spatial variability of the CES in the Shendong mining area was obvious,and the contribution of the change in the low-variable area to the change in the CES was higher than that of the medium-variable area and the abrupt change area,and the CES spatial change was closely related to vegetation cover and land use types.③ The spatial clustering of CES in the Shendong mining area was obvious,showing a pattern of “weakest in the northwest,strongest along the rivers,and insignificant in the southeast”.④ The driving factors of CES change in Shendong mining area were land use type,slope,elevation,rainfall and vegetation coverage in order.The synergy of two factors was higher than that of single factor,and the synergy between land use and other factors was the strongest.At the mine scale,① the CES in the Shendong mine area was highest in the medium-intensity mining area (SCE=0.502 8) and lowest in the very high-intensity mining area (SCE=0.430 8).② The CES in the Bulianta mine area was positively influenced by ecological management measures,the CES in the Daliuta and Huojitu mine area had been negatively affected by mining since 2010,and the CES in the Shigetai,Wulanmulun,Halagou and Yujialiang mine area had continued to suffer negative impacts since mining.③ The CES in the Daliuta rec-lamation experimental area had developed in the direction of becoming stronger.The model’s comprehensive as-sessment results can quantitatively reflect the changing pattern of the CES in the Shendong mining area.It is suggested that Shendong mining area should implement ecological management with the northwest as the key area,and focus on optimizing the land use structure by improving vegetation cover,and use scientific methods such as microbial reclamation in the mining area.In addition,the development and use of multi-scale integrated model for the optimization of multiple ecosystem services should be committed,with a view to providing more accurate and reliable decision support for the sustainable management of regional ecosystem services.

     

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